Personal identification device and method

ABSTRACT

The invention aims at providing personal identification in environments where non-contact is required, with high accuracy even though using a finger vein pattern images unclear and susceptible to positional deviations, wherein it has: a means for acquiring finger vein patterns without contact; a means for carrying out rotational correction using the outline of a finger as a method of taking out a vein pattern contained in the acquired image; a means for normalizing the position of the finger image with reference to the fingertip; a means for acquiring an overall vein pattern statistically by repetitively tracking regions of dark luminance intensities for a desired length from a desired position in the image; a matching means for comparing regions where vein patterns manifest vivid features; and a means for independent matching of subregions and evaluating positional deviations where matching is recognized.

CROSS-REFERENCES

This is a continuation application of U.S. Ser. No. 11/907,421, filedOct. 12, 2007 (now U.S. Pat. No. 7,627,145), which is a continuationapplication of U.S. Ser. No. 11/896,664, filed Sep. 5, 2007 (now U.S.Pat. No. 7,599,523), which is a continuation application of U.S. Ser.No. 11/208,534, filed Aug. 23, 2005 (now U.S. Pat. No. 7,280,676), whichis a continuation application of U.S. Ser. No. 09/945,670, filed Sep. 5,2001, (now U.S. Pat. No. 6,993,160). The entire disclosures of all ofthe above-identified application are hereby incorporated by reference.

This application claims priority to JP 2000-274987, filed Sep. 6, 2000.

BACKGROUND OF THE INVENTION

The present invention relates to a device and a method for identifying aperson by utilizing a vein pattern obtained by imaging light transmittedthrough his or her finger.

Personal identification techniques include methods based onfingerprints, irises, voice, veins on the back of a hand and so forth. Anumber of companies are already manufacturing and marketingfingerprint-based personal identification devices. These productsidentify a person by reading his or her fingerprint by having thefingerprint come into contact with a fingerprint sensor, recognizing endpoints and branching points of the fingerprint, and collating them withcharacteristic points of registered fingerprints.

JP-A-295674/1998 discloses a personal identification device based onveins on the back of a hand. According to this, the back of a hand isfaced toward an image pick-up camera, and the reflection of the lightemitted from the camera is used to pick up a blood vessel pattern toidentify the person on that basis. The device is designed to prevent thelocation of the hand to be imaged from fluctuating from one round ofidentification to another by having the hand grasp a fixed rod-shapedguide.

JP-A-21373/1995 discloses a personal identification device based onfinger veins, which, particularly to reduce the loss of luminous energyat the time of image picking up, keeps an optical fiber in close contactwith the finger and picks up a finger image.

SUMMARY OF THE INVENTION

The prior art uses methods highly likely to meet psychologicalresistance from the person to be identified, such as taking the person'sfingerprint or projecting a light beam into his or her eye. Either ofthe above-cited personal identification devices according to the priorart requires part of the person's body to get in contact with theidentification device, and this may make the identification devicesunsuitable for use in medical care facilities, where sanitation is ofparticular importance. Furthermore, as they utilize features exposedoutside the human body, these devices are susceptible to forgery.

The present invention is intended to architect a security system inenvironments where non-contact is required, such as a medical carefacilities. For this purpose, the invention provides a device and amethod for carrying out personal identification by picking up a fingerimage in a non-contact manner and extracting the vein pattern of theimage from this finger image.

The invention further takes note of a new problem that, where a fingerimage is to be picked up, it is susceptible to rotation or luminanceintensity fluctuations and therefore difficult to identify the personwith high accuracy. Accordingly, the invention provides a device and amethod for carrying out personal identification with high accuracy eventhough it uses a pattern of finger veins susceptible to rotation orluminance fluctuations.

In order to achieve these objects, a personal identification deviceaccording to the invention has a storage for storing vein patterns ofregistered finger images, an interface equipped with a light source anda camera for picking up transmitted light through fingers, and a meansfor extracting a vein pattern contained in the picked-up image oftransmitted light through the fingers and identifying a person bycollating the extracted vein pattern with the vein patterns ofregistered finger images, wherein the interface has a groove into whichfingers are inserted without contact, and the light source and thecamera are arranged opposite each other with the groove between them.

The means for personal identification is characterized in that thepicked-up finger image is corrected for any rotation on the plane ofimage pick-up arising when the fingers are inserted into the interface,and the person is identified by extracting a vein pattern contained inthe finger image corrected for the rotation.

These and other objects, features and advantages of the presentinvention will become more apparent in view of the following detaileddescription of the preferred embodiments in conjunction withaccompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an example of system configuration for implementingthe present invention;

FIG. 2 illustrates an example of configuration of an input interface foracquiring a finger vein image;

FIG. 3 illustrates another example of configuration of an inputinterface for acquiring a finger vein image;

FIG. 4 illustrates an example of finger vein pattern input interfaceembodying consideration for safety;

FIG. 5 illustrates an example of arrangement of a light source and acharge coupled device (CCD) camera in an input interface for imaging avein pattern in many directions;

FIG. 6 illustrates an example of system configuration enablingnon-contact entrance/exit including personal identification;

FIG. 7 illustrates an example of system configuration for carrying outpersonal identification by combining a vein pattern with personalfeature information including a personal identification number (PIN),fingerprint, iris, voice, handwriting and face;

FIG. 8 illustrates an example of system configuration for acquiring atemplate image of a vein pattern by utilizing an IC card;

FIG. 9 is a flowchart showing an outline of processing by software toimplement the invention;

FIG. 10 is an image diagram illustrating a method for tracking theoutline of a finger image;

FIG. 11 is an image diagram illustrating a method for performingrotational correction against any inclination of a finger image;

FIG. 12 is an image diagram illustrating a method for normalizing acut-out part of a finger image;

FIG. 13 is a flowchart showing how a vein pattern is taken out of a anfinger image;

FIG. 14 is a flowchart showing how the ratio of mismatching between twovein patterns is calculated;

FIG. 15 is a flowchart showing how correlation between vein patterns iscalculated by utilizing partial images of two vein patterns; and

FIG. 16 is a table showing performance comparison between a methodaccording to the invention and another method in terms of the falseaccept rate (FAR) and the false reject rate (FRR).

DESCRIPTION OF THE PREFERRED EMBODIMENTS

One embodiment of the present invention will be described in detailbelow. FIG. 1 is a schematic block diagram of a system configuration forimplementing the invention. Within a vein pattern input interface 1,which corresponds to the part into which fingers are to be inserted,there are a light source 2, an optical filter 3 and a CCD camera 4.Insertion of fingers between the light source 2 and the optical filter 3results in acquisition of a vein pattern. Light transmitted throughfingers is picked up by the CCD camera 4 via the optical filter 3. Imagesignals picked up by the CCD camera 4 are taken into a personal computer(PC) 6 by using an image capture board 5. Within the PC 6, the imagesignals that have been taken in are stored into a memory 8 via aninterface 7. A registered image kept in an outer storage 10 is alsostored into the memory 8. Then, in accordance with a program stored inthe memory 8, a CPU 9 determines whether or not the taken-in image isidentical with the registered image. Incidentally, this program may aswell be supplied to the identification device using an outer storagemedium. As the storage medium, for example, a floppy disk, hard disk,optical disk, photomagnetic disk, CD-ROM, CD-R, magnetic tape,nonvolatile memory card or ROM can be used.

FIG. 2 shows an example of structure of the finger vein pattern inputinterface 1 for acquiring a finger vein pattern image by a non-contactmethod. The interface has a finger inlet 22, which is a groove-shapedgap. By passing fingers 20 through that part, a vein pattern isacquired. In doing so, there is no need to bring the fingers intocontact with the identification device itself. Also, by passing aplurality of fingers through the groove, a vein pattern of a pluralityof fingers can be picked up. Furthermore, by swinging down the fingersin an arc track centering on a shoulder, elbow or wrist, it is alsopossible to pick up a finger image by be consecutively passing theplurality of fingers 20 through the finger inlet 22. Where such anon-contact image pick-up method is adopted, the picked-up finger imagerotates relative to the plane of the picked-up image. Therefore, thepicked-up finger image inevitably requires rotational correction.

To add, while the groove may have any direction relative to the ground,especially where the groove is provided in a direction vertical to theground, there is a convenience of use that a patterned image can beacquired by a natural action of the user in which his or her hand isswung following gravity.

Also, the interface structure to let fingers pass through the groove inthis manner has an effect of enhancing the accuracy of identificationbecause rotation around the central axis of any finger is thereby madedifficult.

FIG. 3 shows another example of the finger vein pattern input interface1. This example is an input interface having a hole-shaped finger inlet22. A finger 20 is inserted into a finger inlet 22, within which one ormore each of light sources and imaging devices acquire an image orimages of finger veins. In this process, the vein pattern can as well beacquired by rotating the finger in a coaxial direction around thecentral axis of the finger.

FIG. 4 shows other examples of the non-contact finger vein pattern inputinterface embodying consideration for safety of the person when beingidentified and passing by the installation site of the interface. In(a), there is shown a shape in which the corners of the finger veinpattern input interface are chamfered to ensure the safety of anyfinger, hand, arm and/or the like even if they come into contact. Insome installation site, any projection from the identification devicecould be dangerous. In such a case, arranging the groove laterally asshown in (b) can serve to narrow the width of the projection from theinterface or, as shown in (c), the finger inlet can be bored into thewall itself of the installation site. In (c), however, the groove shouldbe wide enough to let the arm swing down through it. Further, to becompatible with swinging down of the arm and imaging of the fingers, theinner end of the finger inlet can be shaped in an arc to match the trackof the fingers as shown in (d). These structures make it difficult forfingers to come into contact with the identification device when the armis swung in an arc. It is also possible to enhance the safety of fingersagainst contact by covering the surface and finger inlet inside of theidentification device with something soft, such as cushions. This figureillustrates the arrangement of cushions 38 along the arc-shaped part. Toadd, although the groove is cut in the vertical direction and a veinpattern is acquired by having the fingers move in the vertical directionin any of the finger vein pattern input interfaces described above, thegroove can be cut, and the fingers moved, in any desired directiondepending on the conditions of device installation.

FIG. 5 shows an example of configuration for picking up vein patterns inmany directions within the finger vein pattern input interface with aplurality each of light sources and imaging devices. A plurality each oflight sources 2 and CCD cameras 4, each with an optical filter 3, arearranged opposite each other in a coaxial form around the central axisof a finger 20. When the finger 20 is inserted into the interface 1,those imaging devices pick up finger images in many directions. Thisconfiguration has an advantage that vein patterns can be picked up inmany directions without requiring the rotation of the finger. Ifinterference among the light sources disturbs the picked-up images, thelight sources may be operated with time lags for consecutive imaging.

FIG. 6 shows an example of system in which the non-contact finger veinpattern input interface is combined with a non-contact automatic door toenable entrance into and exit out of the room, including identification,to be accomplished without contact. The finger vein pattern inputinterface 1 is installed on a wall beside the automatic door 42, intowhich the finger 20 is inserted. If the vein pattern of a identificationclaimant 40 is found identical with a vein pattern registered with thesystem, the automatic door 42 will automatically open. A majorcharacteristic is that everything from personal identification to theopening/closing of the door then can be accomplished without contact. Asthe input interface in this case, any of the various configuration shownin FIG. 4 can be used.

FIG. 7 shows another example of personal identification device combininga vein pattern with a plurality of identification keys includingfingerprint, iris, voice, handwriting and face. The identificationclaimant 40 is identified by an identification device installed in aplace where he or she is to be identified. Whereas the person's veinsare imaged with the input interface 1 to pick up his or her veinpattern, other personal features are inputted by various inputinterfaces before or after the vein pattern imaging. For instance, theclaimant inputs his or her PIN with a PIN input key 43 and inserts afinger into the vein pattern input interface 1 to get identified. Tofurther enhance the accuracy of identification, the person inputs hisfingerprint with a fingerprint input interface 44, and an iris imagepick-up camera 46 and a face image pick-up camera 48 pick up images ofthe identification claimant's iris and face, respectively. Then to checkhis or her handwriting, the person writes characters on a handwritinginput tablet 52 with a handwriting input pen 50, and a voice the personutters would be picked up by a microphone 54. These diverse personalfeatures are analyzed by the PC 6 to determine finally whether he or sheis to be identified as an authorized person. The way of combination ofpersonal feature information items to be used together with the veinpattern is optional. Although it is obviously unnecessary to use all ofthem, many such items are used in this example to enhance the accuracyof identification. Also, the fingerprint input device and the veinpattern imaging device can be integrated so that both features can beinputted at the same time by having the person to be identified placehis or her finger in a prescribed location only once. This not onlysaves the trouble of the user but also makes possible more accuratepersonal identification.

FIG. 8 shows an example of system using an IC card to provide theidentification device with a PIN and personal feature information. Theidentification claimant 40 has an IC card 60 on which are recorded hisor her PIN, and personal feature information items including the veinpattern, fingerprint, voice, iris, handwriting and face. While thisfigure illustrates an example in which a non-contact IC card is used, itis also possible to use a contact IC card. Information recorded on an ICcard 60 is automatically read into an IC card reader 62 when its bearerapproaches the IC card reader 62. While personal feature information isthen delivered to the personal identification device, it is alsoconceivable to acquire personal feature information by delivering thenonly an identification number for the individual and reading the itemsof personal feature information matching that number out of the personalfeature information stored in the outer storage 10 in advance. In theexample of this figure, a vein pattern is provided as personal featureinformation. After that, a vein pattern is acquired by having the personinsert his or her finger into the finger vein pattern input interface 1,and it is collated with the vein pattern read out of the IC card 60 orthe outer storage 10. If the patterns match each other, the card beareris identified to be an authorized person. Although only a combination ofa vein pattern and an IC card is shown in this figure, it is alsopossible to use in combination various items of personal featureinformation shown in FIG. 7.

The following is a detailed description of a software flow to solve theabove-noted problems, to be executed by the above-described hardware,above all by the CPU 9. Incidentally, the software program forimplementing this flow may as well be supplied to the identificationdevice by using an outer storage medium.

As the storage medium, for example, a floppy disk, hard disk, opticaldisk, photomagnetic disk, CD-ROM, CD-R, magnetic tape, nonvolatilememory card or ROM can be used. FIG. 9 is a schematic flowchart showingthe flow from the time a finger image is taken in until the person isidentified. For personal identification using a vein pattern, it isnecessary to extract a vein pattern from a finger image that is takenin, and compare it with a registered vein pattern. Therefore, apicked-up finger image should go through a number of steps to beconverted into a vein pattern of a form comparable with a registeredimage. First, after going through initialization (200) in various ways,the finger outline is detected (202) to take out only the finger part inthe image. At this point of time, the angle and location in which thefinger is imaged can be detected. After carrying out rotationalcorrection (204) to eliminate any inclination of the finger so that itcan be recognized correctly in whatever angle and location it may beimaged, the finger image is cut out (206). The image acquired thencontains not only the vein pattern but also shades and luminanceunevenness which are unnecessary for identification. Therefore, in orderto take out only the vein pattern, the blood vessel is tracked (208). Byusing its result, global vein pattern matching (210) is performedbetween the registered image and the taken-in finger image, and thecorrelation between the images is computed as an evaluation value.Whereas the claimant is determined to be the authorized person orsomeone else according to the level of the evaluation value, if theevaluation value is near the threshold value (212), local matching (214)is carried out by which each image is divided into subregions, each ofwhich is matched with its counterpart to evaluate deviations in matchinglocations. And final determination is made as to authentication of theperson (216).

A detailed description of each individual item in the flowchart of FIG.9 will follow.

FIG. 10 illustrates an example of detection of the finger outline; (a)is a schematic diagram of a picked-up image. Here will be described acase in which the finger is imaged in the horizontal direction from theleft side of the image and the fingertip is positioned on the rightside. First, contrast is adjusted to emphasize the boundary between thefinger 20 and the background part. However, there is no need to adjustthe contrast of the whole image, but, if for instance the outline of theunder side is unclear, it will be sufficient to adjust the contrast ofonly the under side of the image. This processing emphasizes the edge ofthe finger. How the edge of the finger 20 in (a) can be made more clearis shown in (b).

Then, the detection of the finger outline is carried out actually.First, a tracking point 104 is positioned at the center of an image 100.From this location, the point is shifted upward and downward separatelyby one pixel each, and the starting location for detecting the outlinepart of the finger is determined. As the finger part is shown in themiddle of the image, a few pixels each above and below that location allhave relatively high intensities. As the point is shifted farther upwardand downward, the boundary between the finger part and the backgroundpart is eventually reached. At this time, while the intensities of a fewpixels toward the inside of the image (finger side) are relatively high,those of a few pixels toward the outside of the image (background side)should be low. Therefore, the difference is calculated by subtractingthe sum of the intensities of n outer pixels from the sum of theintensities of the n inner pixels in the current location of thetracking point 104, and the location where the greatest difference valuewas found within the range of the shift of the tracking point 104 to theupper or lower end of the picture can be determined to be the boundarybetween the background and the finger.

Arrival of the tracking point 104 shifting upward and downward atboundaries between the finger and the background is shown in (c). Next,the outline of the finger is tracked from this location. In this case,it has to be tracked in two ways, in the rightward direction and in theleftward direction. When it is tracked in the leftward direction, thedifference between the sum of the intensities of n outer pixels from thesum of the intensities of the n inner pixels should be calculated ateach of three points, to the left, upper left and lower left of thecurrent location, and the point having the greatest difference is chosenas the next location. As the tracking in this way reaches the left endof the image, the locus of the tracking constitutes an outline. Thetracking in the rightward direction has to cover the fingertip part.Therefore, the outline tracking on the upper side should include in itsrange of search a few more pixels to the lower right of the currentlocation and the area straight underneath the current location. Outlinetracking in the under side covers a few more pixels upward to the upperright of the current location and the area straight above the currentlocation. This enables even the curve of a high curvature at thefingertip to be detected.

The final result of the tracking of the finger outline by the trackingpoint 104 is shown in (d). To add, although the foregoing procedure useda simple tracking method because the picked-up image was fixed in form,obviously accuracy can be enhanced by utilizing various other trackingmethods used in image processing.

FIG. 11 illustrates one example of rotational correction processing forthe finger using finger outline information obtained by theabove-described method. An image before rotational correction for thefinger is shown in (a). The inclination of the finger at the time ofimaging can be found out by checking the shape of its outline.Correction to make the inclination constant in every finger imageresults in normalization against two-dimensional rotation relative tothe imaging plane of the camera.

Whereas the inclination of a finger can be regarded as the angle formedbetween an approximated straight line of the finger and a horizon, herewill be explained as an example a method of rotational correctionutilizing the upper outline. The outline of the same line retains thesame shape even if the inclination of its insertion varies. Here will bedetermined an approximated straight line of its outline. Generally, thepositional relationship between a curve and its approximated straightline is constant all the time. Therefore, outlines of the same shapediffering in inclination can be normalized in inclination by theirapproximated straight lines. As the approximation can be made moreaccurate by obtaining the approximated straight line from a curve asclose as possible to a straight line, the approximated straight line isdetermined from the upper outline, which is more nearly straight. Morespecifically, only the part of the outline between a location 16 pixelsfrom the fingertip toward the root of the finger and a location 128pixels ahead in the same direction is used. Deliberate avoidance of thefingertip is intended to stay away from a part having a high curvature.

Next, a few pixels in the outline part to be utilized are picked out atequal intervals, and a straight line 106 approximating the upper outlineis calculated by the least-squares method. Finally the whole is rotatedso as to make this straight line horizontal relative to the image, wherethe center of rotation is supposed to be the junction between thisstraight line and the left edge of the image. Positional normalizationwill be described later. The result of rotational correction to make theapproximated straight line 106 of the upper outline horizontal is shownin (b). FIG. 12 illustrates one example of processing to cut a partrequired for personal identification out of the finger image havingundergone rotational correction. Usually, the locations of a fingerimage in the horizontal and vertical directions differ every time thefinger is imaged. Therefore, in order to facilitate the use of thefinger image for matching, it is necessary to normalize the fingerlocation. On the other hand, for the purpose of recognition, it issufficient for the image to contain a vein pattern, but there is no needto keep other irrelevant parts. Therefore, an image of a smaller sizethan the original image is cut out of the original. In doing so,matching the cut-out location with the same part of the finger all thetime would result in normalization of the location of the finger.Outline information on the finger is used for positioning of the cut-outpart. For positioning in the lateral direction, a fingertip 110 obtainedfrom the outline information is utilized and, for instance, a locationwhere the fingertip 110 coincides with the right edge of the cut-outimage is selected. Next, for positioning in the vertical direction, thecentral axis 108 of the finger is determined by using the upper andlower outlines of the finger, and a position in which the central axis108 passes the center of the cut-out image is selected. Positioning inthis manner gives a cut-out image 114. For this cut-out image 114, thesame part of the finger will be cut out every time whatever location inthe image 100 the finger 20 may be imaged in, and this meansnormalization of the finger location.

FIG. 13 is a flowchart showing the tracking process of the blood vesselin the cut-out finger image. In a finger image picked up by a CCD cameradoes not clearly reveal a vein pattern required for personalidentification. The image that is acquired contains much of informationunnecessary for identification, such as background noise, irregularshades due to the uneven thickness of the finger bone and muscle andintensity fluctuations. Therefore, in order to use such an image forpersonal identification, it is necessary to take out only a vein patternfrom the image or to emphasize the vein pattern. A finger image resultsfrom picking up the light transmitted by the finger. Since thetransmitted light is of a wavelength absorbable by hemoglobin in theblood, the blood vessel part takes on a dark luminous intensity. On theother hand, bright light leaks out of joint parts. Therefore, theluminous intensity of the background significantly varies from one partof space to another, so that mere emphasis of edges cannot emphasize theblood vessel alone. However, in a narrowly localized spatial range, theblood vessel part is darker than its surroundings. Therefore, the locusof continuous shifting from a certain location is highly likely torepresent a blood vessel. Usually a blood vessel does not exist byitself, but there are a plurality of blood vessels, whose number andlengths cannot be known in advance. In this embodiment of the invention,therefore, many loci of diverse lengths will be picked out in manydifferent locations, and they will be superposed over one another tohighlight a single blood vessel pattern in a statistical process.

In accordance with this principle, blood vessels were tracked in thefollowing manner. First, to record the history of blood vessel tracking,a score table of the same size as the image was prepared, and every boxin the table was initialized to 0 (300). In a blood vessel tracking loop(302) executed as many (j) times as necessary for highlighting the wholeblood vessel pattern, first the initial location of the tracking pointfor a single round of blood vessel tracking is determined by a randomnumber (304). However, if the initial location is selected in thebackground, at the fingertip or finger root, or near the finger outline,it would be impossible to correctly track blood vessels. Therefore, theinitial location is selected elsewhere by utilizing information on thefinger outline.

Further, arrangement of the initial location on a blood vessel wouldfacilitate tracking of blood vessels. Accordingly, a plurality ofcandidates for the initial location are selected, and the pixel havingthe darkest luminous intensity among them is determined to be theinitial location. However, if the initial location is determined all thetime in accordance with this condition, it will become difficult totrack blood vessels in a light part. Therefore, pixel having the darkestluminous intensity out of a plurality of candidates for the initiallocation is not always selected as the initial location, but a pixelhaving the lightest luminous intensity is selected as the initiallocation at a certain probability. This probability is determined by arandom number. Next, the direction in which it is easier for thistracking point to shift is determined (306). This attribution is usedfor the determination of a trackable point to be explained afterwards.As one example of method for this determination, the point is determinedby a random number to have a property permitting ready shiftingrightward or leftward and upward or leftward. Then, the “length” oftracking of the tracking point is determined (308), and at the same timeits value is given to the tracking point as its initial value. Trackingis discontinued when tracking has been done for a distance determined bythat length. Thus, the duration of tracking is made the length of thetracking point, and the length is exhausted when each pixel is tracked.The tracking is ended when the length is fully exhausted. This length isdetermined by using a random number.

Then, this tracking point is shifted. At the beginning, a point to whichthe tracking point can shift next is determined (310). Whereas most ofthe blood vessels run in the lengthwise direction of the finger,aligning the shifting direction of the tracking point with the runningdirection of blood vessels results in increased emphasis of the bloodvessels. Therefore, by giving a certain tendency to eligible candidatesfor the destination of next shifting, the shifting tendency of thetracking point is controlled.

As an example of shifting tendency, to facilitate shifting in the rightand left longer axis directions at a probability of 50%, threevicinities on the right or left are selected as trackable points and,for 30% out of the remaining 50%, three vicinities above or below areselected as trackable points to facilitate shifting in the shorter axisdirection of the finger. For the rest, eight vicinities are selected astrackable points. However, in any case, no shifting away from the locustracked so far or outside the finger is allowed. Whereas, trackablepoints are selected in this way, if no trackable point can be found(312), tracking with the current tracking point is ended

Then, the tracking point is shifted to the pixel having the darkestluminance intensity out of the trackable points (314). Then, the currentlocation is registered or updated (316) as locus information so that thecurrent tracking point may not track again the locus it has tracked. Atthis point, the score in the position in the score table correspondingto the coordinates of the pixel is counted up (318). In this case, fivepoints are added, for example. Also, the length, i.e. the trackinglength of the tracking point, is counted down by one (320). It is thenjudged whether or not the tracking point length is zero (322). If it isnot, the process returns to the determination of trackable points (310),and the addition of score points and the updating of locus informationare repeated. When the length has been wholly exhausted, information onthe tracked loci is initialized (324) to complete tracking with thecurrent tracking point. The execution of such a process of blood vesseltracking is repeated many times. Upon completion of this repetition, forpixels tracked a greater number of times, i.e. parts that are moreprobable to be blood vessels, the scores corresponding to thosepositions in the score table are higher. Conversely, locations withlower scores are more probable not to be blood vessels. Therefore, veinpatterns themselves are apparent in this score table. Therefore,grasping this score table as an image would give an image in which onlya vein pattern or patterns are picked out.

In order to render a vein pattern acquired in this way into a form moreconvenient for matching, columns in the score table as a vein patternare classified according to the score count. Herein, they are classifiedinto four categories for example (328). First, no blood vessel issupposed to be present in pixel locations with low scores. Pixellocations with high scores are supposed to be highly likely to representa blood vessel. Pixel locations with medium scores are supposed to beambiguous regions which may, but are not certain to, represent a bloodvessel. Pixels located outside the finger outline are supposed to belongto the background. By matching these four categories with luminousintensities, an image of a vein pattern is acquired.

Finally, in order to fill the blanks of pixels which happened to escapetracking, the blood vessel regions and ambiguous regions were subjectedto expansion (330). The expansion was accomplished by checking, withrespect to all the pixels present in the image, eight vicinities ofpixels in the blood vessel regions and ambiguous regions and, if anynon-blood vessel region in which the number of pixels is four or less,converting that non-blood vessel region into an ambiguous region.

By the foregoing procedure, the score table is converted into a veinpattern image and at the same time into a form more convenient for usein matching. FIG. 14 is a flowchart showing one example of technique forjudging whether or not a vein pattern, acquired by the above-describedmethod, is identical with a registered vein pattern. As an algorithm forcomparing two images, a sequential similarity detection algorithm (SSDA)was adopted. This is a technique, making use of the property ofmismatches to increase monotonously, to discontinue calculation at apoint having surpassed a certain threshold. At the beginning,initialization (400) is carried out in various aspects. Then, one of thetwo vein pattern images is reduced in size by cutting out pixels on thecircumference of the image (402). Then these two images are superposedone over the other, with their central parts aligned, and the luminousintensities of each pair of superposed pixels are compared (404). Then,if a pixel highly likely to represent a blood vessel is superposed overa pixel which is highly unlikely to do so, these pixels are said to bemismatched. The number of these mismatched pixels is counted for thewhole images, though pixels in the larger image having no counterpartsin the smaller image are ignored. The number of mismatches at this timeis regarded as the initial value of the smallest number of mismatches.Then, the images are shifted one pixel or a few at a time within a rangein which no part of the image reduced in size protrudes out of thelarger image (n pixels upward, downward, rightward and leftward from thecenter of the images), and the number of mismatches counted in eachshifted location. In this process, while the number of mismatches iscounted pixel by pixel in the whole images in their current state ofsuperposition (410), if the current smallest number of mismatches hassurpassed even on the way of counting mismatches, the counting isdiscontinued (412) because no smaller number of mismatches can beobtained. If the current number of mismatches does not surpass thesmallest number of mismatches, the smallest number of mismatches in thepast is rewritten into the current number of mismatches (416). After theimages are superposed over each other in the whole range, the smallestnumber of mismatches that is finally obtained is the number ofmismatches between these two images.

Finally, the ratio of mismatching is calculated from this result. First,the sum of the numbers of pixels highly likely to represent a bloodvessel in the two images is calculated (420). For the larger image,however, n pixels in the circumferential region is disregarded. By usingits result and the number of mismatches, the ratio of mismatchingbetween the two vein patterns can be calculated (422). Here, the ratioof mismatching is defined to be the quotient of (the number ofmismatches)/(the total number of pixels highly likely to represent ablood vessel in the two images). If the two vein patterns are the same,the ratio of mismatching is either zero or very small. However, if thevein patterns are different, the ratio of mismatching can be very high.If this value is smaller than a certain threshold, the identificationclaimant is judged to be the authorized person or, if it is higher, heor she is judged to be someone else.

FIG. 15 is a flowchart showing an example of another technique toperform matching in a case where the ratio of mismatching according tothe above-described matching method cannot determine whether or not theindividual is the authorized person. A technique of calculatingmismatches in whole images can accomplish personal identification inmany cases. However, there are some ambiguous data around the threshold.Then, data around the threshold can be assessed by another matchingtechnique, and the overall accuracy of personal identification is likelyto be enhanced.

Local matching is accomplished in the following manner. One of the twocompared images is divided into m (m≦2) subregions (502). In each of thesubregions, matching with the other image is performed once again (506).Here, simply the number of pixels having found counterparts ofrespectively the same luminous intensities is counted. The location inwhich the greatest number of pixels are found matched is regarded as thematching location. The range of shifting is restricted in advance sothat coincidental matching with an evidently impossible location may notoccur. Then, locational information on the best matched subregion isacquired (508). Thus, the extent of deviation of matching in eachsubregion from the initial location is held in the form of atwo-dimensional vector. Upon completion of matching for every subregion,information on m matching locations is plotted on a plane (512), and thedegree of concentration of points is evaluated. If these points aredensely concentrated, it means a close correlation between the twoimages or, conversely, if they are sparse, almost no correlation isconceivable. For the evaluation of the degree of concentration, a weightp is added to each plotted point, and a value smaller by Δp each isadded per pixel of deviation from that point (514). Greater valuesemerge on the plane where plotted points are concentrated, because theweight is added repeatedly. If the matching locations are the same inall the m subregions, the maximum value of the weight that is added willbe m*p. Or, conversely, if the matching locations are sparse, themaximum evaluation value will be p. Since there can be overlapping ofmatching locations by chance, the maximum evaluation value can begreater than p even between images without correlation between them.Scores are assigned on the plane in this way, and the greatest score issought for (516). This score represents the correlation between the twovein patterns. If this count is high, the identification claimant ishighly likely to be the authorized person or, conversely, if the countis low, the claimant is highly likely to be someone else. However, theremay be a high level of correlation by reason of coincidence of matchinglocations by chance. Then, it is highly likely for an unauthorizedperson to be mistaken for the authorized. For this reason, if there areonly a few plotted points within a circle of a certain radius from thelocation where the maximum evaluation value arises, the high evaluationvalue will be judged as being accidental (518), and the claimant isjudged to be an unauthorized person (520). FIG. 16 shows the result ofperformance evaluation according to the present invention and that byanother method. The latter method differs from the invention in theprocess from the acquisition of the finger image until the end ofidentification. By this method, the acquired image is uniformly filteredto emphasize the vein pattern, two-dimensional convolution calculationis applied to a registered template and the image, and the sharpness ofthe peak in the short axis direction of the finger is evaluated. Inperformance evaluation, four images of the fifth finger of each of 678subjects were picked up, one of which was deemed to be the registeredtemplate, and finger images of the authorized person and others werecollated. The collation was carried out by trying every combination ofthe registered template of every subject with the vein pattern of theauthorized person and those of others. Also, collation was also donebetween a finger image which was not the registered template and theregistered template of the same person.

As a result of collation, the false reject rate (FRR), i.e. the rate ofmistaking the authorized person for someone else and the false acceptrate (FAR), i.e. the rate of accepting an unauthorized person as theauthorized, are determined. Here is used as the indicator of performanceevaluation the relationship between the FRR and the FAR. The result ofcomparative performance evaluation in which, in collating the registeredtemplates and other images of respectively the same persons, only oneother image each was used are listed in (a). The smaller the FRR and theFAR the better, but it is seen that the FRR and the FAR according to theinvention are already about 1/10 of the respective rates resulting fromcollation by the other method. Even better results were obtained wherelocal matching was also carried out. The result of comparativeperformance evaluation in which, in collating the registered templatesand other images of respectively the same persons, the image giving thebest result in each case out of three other images was selected arelisted in (b). While, according to this alternative method, there stillare data which do not permit correct distinction between the authorizedand unauthorized persons, the technique according to the invention cancorrectly distinguish the authorized person from others. These resultsendorse the significant advantages of the invention.

According to the present invention, personal identification is possibleusing features within the human body without requiring bodily contactwith the identification device, meeting little psychological resistancefrom the person to be identified, and with little risk of forgery. Inspite of positional deviation intrinsic to the absence of contact andthe use of unclear images, personal identification is made possible withhigh accuracy.

While the present invention has been described above in conjunction withthe preferred embodiments, one of ordinary skilled in the art would beenabled by this disclosure to make various modifications to thisembodiments and still be within the scope and spirit of the invention asdefined in the appended claims.

1. A personal identification system for executing a personalidentification based on information of an IC card, the systemcomprising: an IC card reader for reading a registered featureinformation from the IC card without contacting the IC card; and apersonal identification device for executing the personal identificationbased on the registered feature information read from the IC cardreader, wherein the personal identification device has a light sourcefor applying a light to a hand, an interface for providing an area ofthe hand irradiated by the light in a non-contacting manner, an imagingdevice for imaging the light applied to the hand, and a calculation unitfor extracting a feature information including a vein pattern imaged bythe imaging device, and wherein the calculation unit executes thepersonal identification based on the registered feature information andthe extracted feature information.
 2. A personal identification systemfor executing a personal identification, the system comprising: an ICcard recording a registered feature information; an IC card reader forobtaining the registered feature information from the IC card withoutcontacting the IC card; and a personal identification device forexecuting the personal identification based on the registered featureinformation obtained from the IC card reader; wherein the personalidentification device has a light source for applying a light to a hand,an interface for providing an area of the hand irradiated by the lightin a non-contacting manner, an imaging device for imaging the lightapplied to the hand, and a calculation unit for extracting a featureinformation including a vein pattern imaged by the imaging device, andwherein the calculation unit executes the personal identification basedon the registered feature information and the extracted featureinformation.
 3. A personal identification system for executing apersonal identification based on information of an IC card, the systemcomprising: an IC card reader for reading a registered information fromthe IC card without contacting the IC card; a personal identificationdevice for executing the personal identification based on the registeredinformation read from the IC card reader; and a storage device; whereinthe personal identification device has a light source for applying alight to a hand, an interface for providing an area of the handirradiated by the light in a non-contacting manner, an imaging devicefor imaging the light applied to the hand, and a calculation unit forextracting a feature information including a vein pattern imaged by theimaging device, and wherein the calculation unit reads out from thestorage device a feature information corresponding to the registeredinformation, and executes the personal identification based on the readout feature information and the extracted feature information.
 4. Thepersonal identification system according to claim 1, wherein thepersonal identification device further includes an extracting unit forextracting at least one of a fingerprint, iris, voice, handwriting andface as a second feature information, and wherein the IC card stores aregistered feature information corresponding to the second featureinformation.
 5. The personal identification system according to claim 2,wherein the personal identification device further includes anextracting unit for extracting at least one of a fingerprint, iris,voice, handwriting and face as a second feature information, and whereinthe IC card stores a registered feature information corresponding to thesecond feature information.
 6. The personal identification systemaccording to claim 3, wherein the personal identification device furtherincludes an extracting unit for extracting at least one of afingerprint, iris, voice, handwriting and face as a second featureinformation, and wherein the storage device stores a registered featureinformation corresponding to the second feature information.